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A bi-objective heuristic approach for green identical parallel machine scheduling

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  • Anghinolfi, Davide
  • Paolucci, Massimo
  • Ronco, Roberto

Abstract

Sustainability in manufacturing has become a fundamental topic in the scientific literature due to the preeminent role of manufacturing industry in total world energy consumption and carbon emission. This paper tackles the multi-objective combinatorial optimization problem of scheduling jobs on multiple parallel machines, while minimizing both the makespan and the total energy consumption. The electricity prices vary according to a time-of-use policy, as in many cases of practical interest. In order to face this problem, an ad-hoc heuristic method is developed. The first part of the method, called Split-Greedy heuristic, consists in an improved and refined version of the constructive heuristic (CH) proposed in Wang, Wang, Yu, Ma and Liu (2018). The second part, called Exchange Search, is a novel local search procedure aimed at improving the quality of the Pareto optimal solutions. The experimental results prove the effectiveness of the proposed method with respect to three competitors: CH, NSGA-III, and MOEA/D.

Suggested Citation

  • Anghinolfi, Davide & Paolucci, Massimo & Ronco, Roberto, 2021. "A bi-objective heuristic approach for green identical parallel machine scheduling," European Journal of Operational Research, Elsevier, vol. 289(2), pages 416-434.
    • Handle: RePEc:eee:ejores:v:289:y:2021:i:2:p:416-434
    DOI: 10.1016/j.ejor.2020.07.020
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    References listed on IDEAS

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    Cited by:

    1. Massimo Bertolini & Francesco Leali & Davide Mezzogori & Cristina Renzi, 2023. "A Keyword, Taxonomy and Cartographic Research Review of Sustainability Concepts for Production Scheduling in Manufacturing Systems," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    2. Gaggero, Mauro & Paolucci, Massimo & Ronco, Roberto, 2023. "Exact and heuristic solution approaches for energy-efficient identical parallel machine scheduling with time-of-use costs," European Journal of Operational Research, Elsevier, vol. 311(3), pages 845-866.
    3. Lotfi Hidri & Ali Alqahtani & Achraf Gazdar & Belgacem Ben Youssef, 2021. "Green Scheduling of Identical Parallel Machines with Release Date, Delivery Time and No-Idle Machine Constraints," Sustainability, MDPI, vol. 13(16), pages 1-30, August.
    4. Catanzaro, Daniele & Pesenti, Raffaele & Ronco, Roberto, 2021. "Job Scheduling under Time-of-Use Energy Tariffs for Sustainable Manufacturing: A Survey," LIDAM Discussion Papers CORE 2021019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Catanzaro, Daniele & Pesenti, Raffaele & Ronco, Roberto, 2023. "Job scheduling under Time-of-Use energy tariffs for sustainable manufacturing: a survey," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1091-1109.
    6. Tan, Barış & Karabağ, Oktay & Khayyati, Siamak, 2023. "Production and energy mode control of a production-inventory system," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1176-1187.
    7. Hu, Yusha & Man, Yi, 2022. "Two-stage energy scheduling optimization model for complex industrial process and its industrial verification," Renewable Energy, Elsevier, vol. 193(C), pages 879-894.

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